docs: def _crop_data(self):
          """
          Crop the ``data`` and ``mask`` to have an integer number of
          background meshes of size ``box_size`` in both dimensions.  The
          data are cropped on the top and/or right edges (this is the best
          option for the "zoom" interpolator).
  
          Returns
          -------
          result : `~numpy.ma.MaskedArray`
              The cropped data and mask as a masked array.
          """
  
          ny_crop = self.nyboxes * self.box_size[1]
          nx_crop = self.nxboxes * self.box_size[0]
          crop_slc = index_exp[0:ny_crop, 0:nx_crop]
          if self.mask is not None:
              mask = self.mask[crop_slc]
          else:
              mask = False
  
          return np.ma.masked_array(self.data[crop_slc], mask=mask)